Update docs

docs/source/index.rst

@@ -75,6 +75,7 @@ traditional functions with different dimensions are implemented.
 
    pages/quick_start.rst
    pages/integrated.rst
+   pages/visualization.rst
    pages/categories.rst
 
 

docs/source/pages/support.rst

@@ -6,6 +6,15 @@ If you are using opfunu in your project, we would appreciate citations:
 
 ::
 
+	@article{Van_Thieu_2024_Opfunu,
+		author = {Van Thieu, Nguyen},
+		title = {Opfunu: An Open-source Python Library for Optimization Benchmark Functions},
+		doi = {10.5334/jors.508},
+		journal = {Journal of Open Research Software},
+		month = {May},
+		year = {2024}
+	}
+
 	@software{thieu_nguyen_2020_3711682,
 	  author       = {Nguyen Van Thieu},
 	  title        = {Opfunu: An Open-source Python Library for Optimization Benchmark Functions},

docs/source/pages/visualization.rst

@@ -0,0 +1,71 @@
+Visualization
+=============
+
+Inside Function
+---------------
+
+You can use our visualization module to draw our function.
+
+Code::
+
+	from opfunu.cec_based import F12010
+
+	# Visualize opfunu function using method in object
+	f0 = F12010()
+
+	f0.plot_2d(selected_dims=(2, 3), n_points=300, ct_cmap="viridis", ct_levels=30, ct_alpha=0.7,
+	           fixed_strategy="mean", fixed_values=None, title="Contour map of the F1 CEC 2010 function",
+	           x_label=None, y_label=None, figsize=(10, 8), filename="2d-f12010", exts=(".png", ".pdf"), verbose=True)
+
+	f0.plot_3d(selected_dims=(1, 6), n_points=500, ct_cmap="viridis", ct_levels=30, ct_alpha=0.7,
+	           fixed_strategy="mean", fixed_values=None, title="3D visualization of the F1 CEC 2010 function",
+	           x_label=None, y_label=None, figsize=(10, 8), filename="3d-f12010", exts=(".png", ".pdf"), verbose=True)
+
+	## Visualize opfunu function using utility function
+	from opfunu import draw_2d, draw_3d
+
+	draw_2d(f0.evaluate, f0.lb, f0.ub, selected_dims=(2, 3), n_points=300)
+	draw_3d(f0.evaluate, f0.lb, f0.ub, selected_dims=(2, 3), n_points=300)
+
+
+Custom Function
+---------------
+
+You can also use our visualization module to draw your custom function.
+
+Code::
+
+	from opfunu import draw_2d, draw_3d
+
+	## Define a custom function, for example. I will use mealpy problem as an example
+	from mealpy import Problem, FloatVar
+	import numpy as np
+
+	# Our custom problem class
+	class Squared(Problem):
+	    def __init__(self, bounds=None, minmax="min", data=None, **kwargs):
+	        self.data = data
+	        super().__init__(bounds, minmax, **kwargs)
+
+	    def obj_func(self, solution):
+	        x = self.decode_solution(solution)["my_var"]
+	        return np.sum(x ** 2)
+
+	bound = FloatVar(lb=(-10., )*20, ub=(10., )*20, name="my_var")
+	custom_squared = Squared(bounds=bound, minmax="min", data="Amazing", name="Squared")
+
+	## Visualize function using utility function
+	draw_2d(custom_squared.obj_func, custom_squared.lb, custom_squared.ub, selected_dims=(2, 3), n_points=300)
+	draw_3d(custom_squared.obj_func, custom_squared.lb, custom_squared.ub, selected_dims=(2, 3), n_points=300)
+
+
+.. toctree::
+   :maxdepth: 4
+
+
+.. toctree::
+   :maxdepth: 4
+
+
+.. toctree::
+   :maxdepth: 4